@GigaAI

Reprogram each of the world’s largest companies using AI, reaching every person on Earth.

 San Francisco, CA
giga.ai
Joined July 2023
  • Tweets58
  • Following3
  • Followers6.7K
5Media
Pinned Tweet
Giga
@GigaAIJul 14
Everyone is trying to build a support agent. Now you can build one in your CLI that resolves 90% of your support tickets. Today we're launching the Giga CLI. pip install giga-sdk Build, test, deploy, and roll back your AI agents like production software. This is the workflow our customers use to operate AI agents resolving 100,000+ support tickets every day. → CI-gated deployments → GitHub-powered knowledge base syncs → Bulk conversation analysis → Integrating Coding Agents directly into Giga Available now on PyPI.
12
10
2
94
213,230
The @GigaAI team just keeps shipping high-quality design 👏
1
2
1
10
1,085
Today we’re launching scheduled callbacks for Giga voice agents. Your agent reaches someone who is walking into a meeting. They say, “Call me at three.” Giga schedules the callback and resumes the conversation when it works best for your customer.
2
1
6
1,644
Interruptions aren’t a barrier anymore: giga.ai/news/scheduled-callb…

Scheduled callbacks for Giga voice agents | Giga

Giga’s voice AI agents can now schedule and place callbacks on their own. A customer who gets interrupted mid-call picks a time, and the agent calls back then — carrying the conversation’s context...

giga.ai
419
Introducing Scout in Slack. Every dashboard eventually leads to a Slack thread. Whether its containment dropping, CSAT falling, or escalations spiking, there's always a thread where your team asks: "Can someone look into this?" That's the moment the real work starts. Scout for Slack investigates the metric: ➡️Reads the conversations ➡️Finds the pattern ➡️Identifies the workflow ➡️Recommends the fix ➡️Validates it before deployment Dashboards tell you what changed. Scout tells you why. Find out more in the comments⬇️
2
6
888
Read more: giga.ai/news/scout-in-slack

Scout, now in Slack | Giga

Every support investigation starts with someone asking a question in Slack, and ends with someone reading tickets by hand. Scout is an autonomous investigator that does that work in the thread where...

giga.ai
2
425
Check it out: giga.ai/cli

Giga CLI: Ship and Operate AI Support Agents from the Terminal | Giga

Find a failed ticket, ask Scout why, ship the fix and check the impact, all from your terminal. MIT-licensed, on PyPI: pip install giga-sdk.

giga.ai
2
1,215
Growth has traditionally meant hiring more people, adding more software, or launching more campaigns. GigaML's Scout takes a different approach by focusing on the conversion point that matters most to your business. It keeps running experiments, learning from results, and compounding thousands of small improvements into meaningful business outcomes!
🤝 Paid partnership
Giga
@GigaAIJun 29
Introducing Scout. Tell it the KPI you care about, like funded deposits, and it builds the agents, learns from every conversation, tests each change, and keeps improving that number on its own. You set the goal. Scout gets you there.
4
1
23
13,148
Scout can help you set your goals with plain natural language, so even greg can use Giga
greg
@greg16676935420Jun 29
I have no idea what a KPI is and at this point I’m too afraid to ask Does anyone know what it even stands for?
1
7
3,046
The future is heading here: agents configuring agents. Expertise, even of this meta kind, is becoming accessible through AI.
Giga
@GigaAIJun 29
Introducing Scout. Tell it the KPI you care about, like funded deposits, and it builds the agents, learns from every conversation, tests each change, and keeps improving that number on its own. You set the goal. Scout gets you there.
1
7
2,047
Autoresearch is cool until you start climbing the wrong hills. Every business is different, and the hills you climb are unique. Giga’s KPIs lets you climb a hill which matters to your business. Read more at giga.ai/scout

Scout: Automatically Improve Support KPIs with AI | Giga

Scout learns from every conversation and improves the KPI you define, on autopilot.

giga.ai
Giga
@GigaAIJun 29
Introducing Scout. Tell it the KPI you care about, like funded deposits, and it builds the agents, learns from every conversation, tests each change, and keeps improving that number on its own. You set the goal. Scout gets you there.
2
2
13
3,472
Introducing Scout. Tell it the KPI you care about, like funded deposits, and it builds the agents, learns from every conversation, tests each change, and keeps improving that number on its own. You set the goal. Scout gets you there.
51
33
34
754
1,488,166
Check it out: giga.ai/scout

Scout: Automatically Improve Support KPIs with AI | Giga

Scout learns from every conversation and improves the KPI you define, on autopilot.

giga.ai
1
5
158
266,714
Honored to join the list!
Harmonic
@harmonic_aiJun 16
❗New Harmonic Hot 25❗ @resolveai joins @Lovable as the only two startups to top the Harmonic Hot 25 twice! This comes after a $40M April extension of their Series A, this time at a $1.5B valuation. Up 50% form the February round. Thousands of investors use Harmonic every day. These are the startups they’re watching most closely as we approach Q3. harmonic.ai/hot-25-startup/q…
4
2,392
lots of great startup lessons from @varunvummadi leading Giga. quickly becoming a generational company that is taking down some formidable competitors. Great having him at Startup School in India earlier this year!
Y Combinator
@ycombinatorMay 29
Varun Vummadi (@varunvummadi) is the co-founder of @GigaAI, which builds AI agents for customer support for some of the biggest companies in the world, including DoorDash, one of the largest crypto exchanges in the US, and a top-three global telecom provider. At Startup School India, Varun sat down with YC's @agupta to talk about why he turned down a high-paying quant job to start a company, the multiple pivots it took to find the right problem, and how their small team of eight beat a 400-person competitor to land a contract with DoorDash. 01:33 — Early Days & Origin Story 03:37 — The YC Interview Disaster 06:28 — Pivoting Away From EdTech 07:25 — Finding the Real Idea 08:39 — Beating a Well-Funded Competitor 10:00 — Winning DoorDash With 8 People 11:09 — What GigaML Looks Like Now 12:40 — Advice for College Students 15:51 — Why Charge Early? 17:33 — The Next Big Bet 18:43 — Running the Company on AI 20:19 — How They Hire Engineers 22:04 — Product Over Sales 23:37 — Burn the Boats
4
15
96
32,144
Varun Vummadi (@varunvummadi) is the co-founder of @GigaAI, which builds AI agents for customer support for some of the biggest companies in the world, including DoorDash, one of the largest crypto exchanges in the US, and a top-three global telecom provider. At Startup School India, Varun sat down with YC's @agupta to talk about why he turned down a high-paying quant job to start a company, the multiple pivots it took to find the right problem, and how their small team of eight beat a 400-person competitor to land a contract with DoorDash. 01:33 — Early Days & Origin Story 03:37 — The YC Interview Disaster 06:28 — Pivoting Away From EdTech 07:25 — Finding the Real Idea 08:39 — Beating a Well-Funded Competitor 10:00 — Winning DoorDash With 8 People 11:09 — What GigaML Looks Like Now 12:40 — Advice for College Students 15:51 — Why Charge Early? 17:33 — The Next Big Bet 18:43 — Running the Company on AI 20:19 — How They Hire Engineers 22:04 — Product Over Sales 23:37 — Burn the Boats
32
24
9
354
151,160
Introducing hallucination correction. We have reduced hallucination by 70%. Giga's hallucination rate is at ~1%. Better than the best frontier models. Deploy AI your customers can trust.
35
30
34
431
1,226,472
Learn more at giga.ai/hallucinations

Real-Time Hallucination Correction at Zero Latency Cost — Giga

We reduced voice agent hallucination rates from 4-5% to less than 1% in production without adding latency. LLMs generate text faster than humans can speak it. That speed gap is where we run detection.

giga.ai
1
3
21
83,154
Check out our CTO's technical blog as well: xitter.cf/eshamanideep/status/20…
Esha
@eshamanideepMay 7

Real-Time Hallucination Correction at Zero Latency Cost

Article · @eshamanideep
1
16
61,443
“Most people fine-tune models for two reasons: cost and speed.” @varunvummadi CEO of @GigaAI: “Fine-tuning reduces cost, increases speed, and improves throughput.” “Some industries like healthcare and finance also prefer it because they don’t want to rely on closed-source models.” “But when we looked at the data, two use cases dominated: support and coding.” “So we decided to focus on support and double down there.”
5
8
2,502
Load more